Want to Succeed at Data-Driven Transformation? Start Slow

Data-driven transformation efforts often fail because companies are moving too fast or too slow. If they're racing into it, they're probably not getting the details right. If they're trying to get everything into a perfect state before doing anything, they're wasting precious time. Either way, ROI suffers.

If you want to strike the right balance, you have to think carefully about what you want to do and why you want to do it. You also have to move at an appropriate speed which means balancing short-term and long-term goals.

Start small

Boston Consulting Group recently published an in-depth article about data-driven transformation. In it, the authors raise a lot of good points, one of which is taking small steps rather than giant leaps.

Taking small steps enables businesses to succeed more often, albeit on a smaller scale. If the project is a success, the money saved or earned can be used to fund subsequent steps. Small successes also help keep teams motivated. However, executing too many small projects simultaneously can be counterproductive.

"The first mistake I see is doing 200 proof of concepts. The second thing I see is people start to do a pilot, even at scale, but [they think] first we need a developer to reinvent the system and then we'll get the value at the end," said Antoine Gourévitch, a Senior Partner and Managing Director at BCG. "I'd rather find a quick and dirty way to connect the IT systems and get [some immediate value] rather than doing a full transformation. You can have a transformation over three to five years, but at least I need to do the connection between my pilot at scale and the dedicated systems for the data platform that's needed to be of value as we go."

The third challenge is prioritizing pilots or projects. Value is the criteria there. Without a prioritized roadmap, "cool" projects may take precedence over projects that deliver business value.

Three steps to better ROI

BCG offers a lot of good advice in its article, not the least of which is breaking short-term and long-term goals into a three-step process that enables quick wins while paving the way to data-driven transformation. The three steps are:

Antoine Gourevitch, BCG

Within those three steps, BCG specified actions companies should take. Upon close review, it's clear that some of the recommended actions, such as "fail fast," apply to more than one step. If you read BCG's article and ponder the graphics, it will get you thinking about how to scale success in your organization.

BCG also presents a five-level transformation model that includes vision, use cases, analytics, data governance and data infrastructure. Gourévitch said data governance tends to be the most problematic because data isn't viewed as a corporate asset, so data owners may hesitate to share it.

Bottom line

Companies often move too fast or too slow when becoming data-driven organizations. When they move too fast, they can overlook important details that cause initiatives to fail. When they move too slow, they risk losing competitive advantages.

Somewhere between 200 pilots and one massive transformation effort is a balance of short-term and long-term goals, investment and ROI. The challenge, as always, is finding the balance.